Multi-taxa ecological responses to habitat loss and fragmentation in western Amazonia as revealed by RAPELD biodiversity surveys
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT Habitat loss and fragmentation caused by deforestation are important anthropogenic drivers of changes in biodiversity in the Amazon rainforest, and has reached its highest rate in recent decades. However, the magnitude and direction of the effects on species composition and distribution have yet to be fully understood. We evaluated the responses of four taxonomic groups − birds, amphibians, orchid bees, and dung beetles - to habitat loss and fragmentation at both species and assemblage level in the northern Ecuadorian Amazon. We sampled fifteen 250-m long plots in terra-firme forest remnants. We calculated one landscape fragmentation index (fragindex), which considers the proportion of continuous forest cover, edge density and isolation in the landscape, and nine landscape configuration metrics. Logistic regression models and multivariate regression trees were used to analyze species and assemblage responses. Our results revealed that over 80% of birds, amphibians or orchid-bee species, and 60% of dung beetles were negatively affected by habitat loss and fragmentation. Species composition of all taxonomic groups was significantly affected by differences in forest cover and connectivity. Less than 5% of all species were restricted to landscapes with fragindex values higher than 40%. Landscape metrics related to the shape and area of forest patches determined the magnitude and direction of the effect on species responses. Therefore, changes in the landscape configuration of Ecuadorian Amazonia should be minimized to diminish the effects of habitat loss and fragmentation on species occurrence and assemblage composition.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it